An Uncertainty-Based Voltage Control Model of a Smart Active Network in the Presence of Electric Vehicles: A Distributed Optimization Approach

Nowadays, Distributed Energy Resources (DERs) and Electric Vehicles (EVs) are being increasingly used in smart distribution networks. There are concerns regarding the use of DERs and EVs which are twofold: (i) they may lead to grid voltage variation and (ii) they have uncertainty in power production. In this paper, a distributed voltage control method is proposed in the simultaneous presence of DERs and EVs preserving the independence and reducing the communications between them while considering probabilistic behaviors. The proposed objective function improves the system voltage profile with the lowest rate of change in the active and reactive power of DERs and EVs. For this purpose, a method is developed for converting the centralized optimization problem to the distributed optimization problem using Dual-Decomposition (DD) and Alternating Direction Method of Multipliers (ADMM) algorithms based on Peer-to-Peer (P2P) communication capabilities of DERs and EVs. The uncertainty of DERs and EVs are modelled by utilizing a scenario-based approach and a Two-Point Estimation Method (2PEM), respectively. The results on the modified IEEE 69-bus test system show that the proposed method can improve the voltage deviation of the worst bus by about 7%, and also reduce grid losses by about 48%.